Patent application number | Description | Published |
20130282595 | METHOD AND APPARATUS FOR OPTIMIZING WEB AND MOBILE SELF-SERVE APPS - An embodiment of the invention takes advantage of the fact that the intuitive power of a self-serve app lies in constant learning. The app must quickly evolve to predict customer needs and provide the right content to the right customer. In an embodiment, Web and mobile self-serve apps are optimized by leveraging the chat data of drop-off customers from each screen of the app. In an embodiment, self-serve drop-off data is combined with chat data, the customer's identity data and Web log data to provide a powerful source for driving the targeting and content optimization of the app. | 10-24-2013 |
20140192971 | METHOD AND APPARATUS FOR ANALYZING LEAKAGE FROM CHAT TO VOICE - The customer experience is enhanced by detecting leakage-to-voice from chats and providing recommendations to operations, chat agents, and customers. A chat is classified into leakage-to-voice or leakage-to-text chat and actionable recommendations are then provided to operations, chat agents, and customers based on the leakage information. Once leakage is identified, various other insights are extracted from chats and such insights are fed into the knowledge-base. Such insights also used in agent training and are provided to chat agents as recommendations. This results in a better customer experience. | 07-10-2014 |
20140195298 | TRACKING OF NEAR CONVERSIONS IN USER ENGAGEMENTS - A computing method and system is disclosed for analyzing interactions between a user and a customer support agent. Typical interactions include inquiries about a product or service, and a service call. When the user purchases a good or service, or successfully completes a service call, the customer converts, e.g. the sales pitch or service solution was successful. If the customer does not convert, then the interaction between user and agent is analyzed to determine why the user did not convert and whether the user should be categorized for potential retargeting. | 07-10-2014 |
20140195378 | STAGE-WISE ANALYSIS OF TEXT-BASED INTERACTIONS - The stages of an interaction between a potential customer (the user) and a sales representative (the agent) during a sales interaction are identified to understand the interaction factors that drive sales and, by doing so, to serve the customer better and thus increase sales. Initially, a user makes contact with an agent via a communications network. During the interaction, a dropping point is reached, i.e. the point in the interaction at which either the user or the agent ends the interaction. The dropping point and other interaction factors is analyzed. Based upon such analysis, various recommendations are made to the agents to improve the user's sales experience. | 07-10-2014 |
20140195562 | DETERMINING PRODUCT CATEGORIES BY MINING INTERACTION DATA IN CHAT TRANSCRIPTS - The propensity and intent of a user to make a purchase is predicted based on product search queries and chat streams. The contents of the data sources, including search queries and chat streams, are analyzed for product names and product attributes. The results of the analyses are used to predict user needs. Product names and attributes are extracted from the data sources. The extracted information is mapped onto abstract product categories. Based on the abstract product categories, offers for products and services are made to the user. | 07-10-2014 |
20140222528 | SEGREGATION OF CHAT SESSIONS BASED ON USER QUERY - Embodiments of the invention relate to chat and, more particularly, to determining an that is to be action taken based on the type of chat session. The resolution of the chat is categorized to decide the necessary steps taken and also to monitor the agent's performance. A chat filter extracts relevant portions of a chat session. The relevant factors are taken into consideration and scored based on the feature vectors. A model is built and the type of resolution is determined. An analysis of the chat session is then performed taking into consideration several factors. | 08-07-2014 |
20150237206 | METHOD AND APPARATUS FOR ANALYZING LEAKAGE FROM CHAT TO VOICE - The customer experience is enhanced by detecting leakage-to-voice from chats and providing recommendations to operations, chat agents, and customers. A chat is classified into leakage-to-voice or leakage-to-text chat and actionable recommendations are then provided to operations, chat agents, and customers based on the leakage information. Once leakage is identified, various other insights are extracted from chats and such insights are fed into the knowledge-base. Such insights also used in agent training and are provided to chat agents as recommendations. This results in a better customer experience. | 08-20-2015 |
20150254675 | METHOD AND APPARATUS FOR PERSONALIZING CUSTOMER INTERACTION EXPERIENCES - A computer-implemented method and an apparatus for personalizing customer interaction experiences receives an input corresponding to at least one of a business objective and a customer interaction channel. A customer classification framework is selected based on the input. The customer classification framework is associated with a plurality of persona types, where each persona type is associated with a set of behavioral traits. A persona type for a customer is predicted from among the plurality of persona types during an interaction on the customer interaction channel. A propensity of the customer to perform at least one action is predicted based on the persona type. A provisioning of personalized interaction experience to the customer is facilitated based on the predicted propensity of the customer to perform the at least one action. | 09-10-2015 |
20150256675 | METHOD AND APPARATUS FOR IMPROVING GOAL-DIRECTED TEXTUAL CONVERSATIONS BETWEEN AGENTS AND CUSTOMERS - In accordance with an example embodiment a computer-implemented method and an apparatus for predicting and tracking of mood changes in textual conversations are provided. The method includes determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer. Changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation are tracked by the processor. Further, the method includes determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics. | 09-10-2015 |